function prob_vec = changepoints(data,G)

% function prob_vec = changepoints(data,parameter_matrix)
% 'convoles' (using neat bayesian result for marginal posterior prob) the parameter matrix with the data.

prob_vec = zeros(length(data) - length(G));
for m = 1:(length(data) - length(G))
	prob_vec(m) = marginal_posterior_probability(data(((m*length(data)+1)-length(data):m*length(data))));
end
	